DESCRIPTION: (Applicant's Description) Cancer will affect one out of every three Americans in their lifetime. Even though advances in research and medicine have given us a greater understanding of cancer it has also revealed the great complexity of this disease. Towards a greater understanding of neoplasms and the formation of neoplastic tissue, there is an interest in the identification of all expressed genetic information of neoplastic cells and to compare this to expressed genetic information in normal cells. This application describes proposed research for the development of innovative technologies for the efficient generation of representational full length cDNA libraries and for the normalization and subtractive enrichment of these libraries. Full Length cDNAs are those clones that contain a copy of the entire mRNA sequence from which they were derived. Representational libraries are libraries that contain at least one cDNA for every mRNA species present in the starting tissue. Of the mRNAs in a typical cell, the prevalent and intermediate frequency classes comprise between 50 to 65 % of the total mRNA mass while representing only about 1000 to 2000 different mRNAs. Redundant identification of mRNAs of these two frequency classes is destined to become overwhelming in a random cDNA discovery program. Thus it is very useful to be able to construct normalized and subtracted libraries. Normalized libraries are libraries which contain a near molar equivalent copy of each mRNA transcript of the RNA source. Subtracted libraries are libraries which contain clones representing the difference between two sources of RNA. The development of these technologies will provide tools for the many investigators who have as their goal the further understanding of the generation of neoplasms and the development of methods for the treatment of these diseases.